2008 ANonParamSemiSupDiscrMeth

(Bondu et al., 2008) ⇒ Alexis Bondu, Marc Boullé, and Vincent Lemaire. (2008). “A Non-parametric Semi-supervised Discretization Method.” In: International Journal on Knowledge and Information Systems (KAIS), (24:1). doi:10.1007/s10115-009-0230-2

Subject Headings: Semi-Supervised Algorithm, Discretization Task.

Notes

Cited By

~5 http://scholar.google.com/scholar?q=%22A+Non-parametric+Semi-supervised+Discretization+Method%22+2008

Quotes

Abstract

Semi-supervised classification methods aim to exploit labelled and unlabelled examples to train a predictive model. Most of these approaches make assumptions on the distribution of classes. This article first proposes a new semi-supervised discretization method which adopts very low informative prior on data. This method discretizes the numerical domain of a continuous input variable, while keeping the information relative to the prediction of classes. Then, an in-depth comparison of this semi-supervised method with the original supervised MODL approach is presented. We demonstrate that the semi-supervised approach is asymptotically equivalent to the supervised approach, improved with a post-optimization of the intervals bounds location.

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2008 ANonParamSemiSupDiscrMeth	Alexis Bondu Marc Boullé Vincent Lemaire			A Non-parametric Semi-supervised Discretization Method			http://perso.rd.francetelecom.fr/boulle/publications/BonduEtAl09.pdf